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Abstract

Background

Inflammatory bowel disease (IBD) involves a breakdown in interactions between the
host immune response and the resident commensal microbiota. Recent studies have suggested
gut physiology and pathology relevant to human IBD can be rapidly modeled in zebrafish
larvae. The aim of this study was to investigate the dysbiosis of intestinal microbiota
in zebrafish models with IBD-like enterocolitis using culture-independent techniques.

Results

IBD-like enterocolitis was induced by exposing larval zebrafish to trinitrobenzenesulfonic
acid (TNBS). Pathology was assessed by histology and immunofluorescence. Changes in
intestinal microbiota were evaluated by denaturing gradient gel electrophoresis (DGGE)
and the predominant bacterial composition was determined with DNA sequencing and BLAST
and confirmed by real-time polymerase chain reaction. Larval zebrafish exposed to
TNBS displayed intestinal-fold architecture disruption and inflammation reminiscent
of human IBD. In this study, we defined a reduced biodiversity of gut bacterial community
in TNBS-induced coliitis. The intestinal microbiota dysbiosis in zebrafish larvae
with IBD-like colitis was characterized by an increased proportion of Proteobacteria (especially Burkholderia) and a decreased of Firmicutes(Lactobacillus group), which were significantly correlated with enterocolitis severity(Pearson correlation
p < 0.01).

Conclusions

This is the first description of intestinal microbiota dysbiosis in zebrafish IBD-like
models, and these changes correlate with TNBS-induced enterocolitis. Prevention or
reversal of this dysbiosis may be a viable option for reducing the incidence and severity
of human IBD.

Keywords:

Background

Inflammatory bowel disease (IBD), broadly classified into ulcerative colitis (UC)
and Crohn’s disease (CD), is a chronic gastrointestinal (GI) illness of uncertain
etiology with high morbidity and relapse. Symptoms range from abdominal pain, weight
loss and diarrhea to ulceration, perforation and complete obstruction of the GI tract.
Although the precise etiology of IBD remains unclear, several factors are believed
to play a role in its development and progression, including host genotype, immune
disequilibrium, the composition of microbial communities resident in the GI tract
and environmental factors [1,2]. In particular, the interactions between intestinal epithelial damage and microbial
incursion have become new research hotspots.

The human intestinal tract plays host to approximately 100 trillion microorganisms,
with at least 15,000-36,000 bacterial species. The intestinal microbiota is now considered
to be a functional organ associated with normal physiological processes, such as metabolism,
immunological response and intestinal epithelium morphogenesis [3-5]. Thus, there are many areas of host health that can be compromised when the microbiota
is drastically altered. IBD clearly involves a breakdown in interactions between the
host immune response and the resident commensal microbiota. Several investigators
have documented changes in the gut microbiota associated with IBD, especially a dramatically
reduced diversity in the phylum Firmicutes and concomitant increase in Proteobacteria[6-8]. In humans, a therapeutic strategy called fecal bacteriotherapy involving transfer
of fecal material from a healthy donor to an IBD patient has successfully ameliorated
the disease [9,10]. That the restoration of microbial diversity is effective suggests the intestinal
microbiota alteration may play a key role in disease pathogenesis. However, our knowledge
of the microbiota shifts associated with IBD is far from complete, and it remains
a question whether these changes are responsible for the origin of IBD, or alternatively,
a direct or indirect consequence.

Murine models, for example, IL-10 deficient (IL-10−/−) mice and dextran sodium sulfate
(DSS)-treated mice, have contributed enormously to understand the pathogenesis of
IBD. Previous reports on DSS-induced colitis in murine models revealed that oral DSS-induced
mucosal injury is more extensive in animals with commensal bacterial depletion compared
to conventionalize counterparts. Contradictory data was seen in IL-10 deficient (IL-10−/−)
mice, showing that IL-10−/− mice fail to develop spontaneous colitis if reared in
germ-free conditions [11-13]. The difference may be caused by a variety of pathogenic mechanism, however, the
research is limited by the time, cost and ethics and a new animal model is in badly
need. The zebrafish model as an established developmental biology model has recently
come to the fore in the study of developmental biology and disease processes. Fleming
et al. developed an IBD-like model in zebrafish larvae using 2, 4, 6-trinitrobenzenesulfonic
acid (TNBS), which enable study of host-bacterial interactions in detail in IBD processes
[14,15]. The zebrafish digestive tract is similar to that of mammals in its development,
organization and function, and observation of the larvae gut following induction of
IBD reveals region specific disease changes with biological, pathological and clinical
relevance to the human condition [14-17]. Additionally, the zebrafish environment is relatively easy to manipulate and embryos
can conveniently be produced in large numbers. Finally, the intestines of the zebrafish
can be embedded in whole for analysis.

Zebrafish are well suited for studying host-bacterial interactions as they have innate
and adaptive immune systems similar to higher vertebrates [18]. Comparative metagenomic profiling of zebrafish and mouse gut microbiota revealed
that they share six bacterial divisions, including Proteobacteria, Firmicutes, Bacteroidetes, Verrucomicrobia, Actinobacteria and Planctomycetes divisions [19]. Besides, microarray analysis of gnotobiotic zebrafish has revealed transcriptional
alterations in response to the microbiota that consistent with mammals, demonstrating
an evolutionarily conserved role of the gut microbiota in vertebrate development [20,21]. Moreover, the resident commensal microbiota in both fish and mice provide similar
functions in the gut: they ferment polysaccharides to short-chain fatty acids (SCFAs)
and play an important role in defense against pathogenic infection [21,22]. In addition, studies in zebrafish gut differentiation show that in the absence of
microbiota, the larvae gut is arrested in specific aspects of differentiation and
altered in specific aspects of its function, which can be reversed by the introduction
of bacteria later in development [5]. Another study revealed alterations on gut microbiota after feeding the zebrafish
dietary probiotic Lactobacillus rhamnosus for 10 days, which has significant effects on the reproductive physiology [23]. All of this suggests that the microbiota in zebrafish gut may play the same role
in disease pathogenesis as in mammals.

The aim of the work reported here was to carry out a molecular analysis on the composition
of the intestinal microbiota in zebrafish larvae with TNBS-induced IBD-like colitis
applying PCR-denaturing gradient gel electrophoresis (DGGE). A range of TNBS doses
and exposure times were investigated in order to find out whether the intestinal epithelial
damage and microbiota alternations in colitis processes are dose and time dependent
fashion. Furthermore, we aimed to identify specific bacterial species of the gut microbiota
that could be associated with the pathogenesis of colitis in zebrafish by DNA sequence
analysis. Consequently, we also revealed the establishment of the resident microbiota
in larval zebrafish gut from individuals of developing fish from 4 dpf to 8 dpf. Within
the present work, we analyzed the zebrafish TNBS-induced enterocolitis in greater
detail and first defined the changes of the intestinal microbiota in zebrafish IBD-like
models, which might provide novel knowledge on the role of intestinal bacterial dysbiosis
in IBD pathogenesis and show technical feasibility of studying host-bacterial interactions
in IBD processes.

Results

Pathological changes in TNBS-induced enterocolitis

The record of the dose-dependent and time-course survivorship of the embryos/larvae
is shown in Figure 1. The treatment of TNBS started from 3 days post fertilization (dpf) until harvest
at 4, 6 or 8 dpf in each TNBS-exposed group. Before 8 dpf, there was no significant
difference in the percentage of survivorship in any of the TNBS-exposed groups compared
to the controls. At TNBS concentrations of 25 and 50 μg/ml, no significant increase
in mortality was observed over the whole exposure time, whereas a slight increase
(p<0.05) in mortality was observed in the dose of 75 μg/ml TNBS.

Figure 1.Effect of different 2, 4, 6-trinitrobenzenesulfonic acid (TNBS) concentrations (0,
25, 50 and 75 μg/ml) in the cumulative survival rate. Zebrafish were exposed to TNBS from 3 days post fertilization (dpf). Results are
representative of three independent experiments. Values are presented as mean ± SEM.

For evaluation of enterocolitis changes caused by TNBS exposure, a simple scoring
system was devised (Table 1). Intestinal bulb, mid-intestine, and posterior intestine were assessed separately.
Total enterocolitis score representing the cumulative values of these separate parameters
for all 3 segments of the intestine is shown in Figure 2A. Zebrafish collected at 4 dpf showed no significant difference between TNBS-treated
and control samples. However, changes were first observed at 6 dpf in the high dose
of 75 μg/ml TNBS exposed larvae (7, compared with 0 in the control group). At 8 dpf,
there was a significant dose-dependent increase in the enterocolitis score of TNBS-exposed
groups (6, 8 and 12 in the dose of 25, 50 and 75 μg/ml, respectively), as compared
with the score of 3 in the control. It demonstrated administration of TNBS to the
embryo medium was able to induce enterocolitis.

Figure 2.Histological analysis of TNBS-induced enterocolitis. A: Total enterocolitis score of larval zebrafish exposed to different TNBS concentrations
(0, 25, 50 and 75 μg/ml) at 4, 6 and 8 dpf. The scores were quantified by a blinded
scorer. For each score, a total of 30 folds (10 per intestinal segment) were evaluated
per intestine and 6 intestines were evaluated for each experimental group from three
independent experiments. All error bars represent as mean ± SEM. n=6 larvae per group,
aIndicates a significant difference (p<0.05) between TNBS-exposed group (25 μg/ml) and the control, bIndicates a significant difference (p<0.05) between TNBS-exposed group (50 μg/ml) and the control, cIndicates a significant difference (p<0.05) between TNBS-exposed group (75 μg/ml) and the control, dIndicates a significant difference (p<0.05) between control groups at 6 dpf and 4 dpf, eIndicates a significant difference (p<0.05) between control groups at 8 dpf and 4 dpf. B: Representative haematoxylin-eosin stained sagittal sections of the whole intestine
tact and regions of the intestinal bulb, the mid-intestine and the posterior intestine
from the statistically significant groups taken at 4, 6 and 8 dpf. In the segment
of the intestinal bulb (ib), the lumen expands and the depth of epithelial folds is
progressively reduced during TNBS exposure (arrows). The mid-intestine is demarcated
by the presence of goblet cells and shows increased numbers with TNBS treatment (arrowheads).
No significant changes are shown in the posterior intestine region between control
and TNBS-exposed samples. a, anus; ib, intestinal bulb; G, gill arches; L, liver;
sb, swim bladder; n, notochord; s, somite. Scale bars, 50 μm.

Representative pictures of the statistically significant groups are shown in Figure 2B. In the intestine bulb, the epithelium of control samples was characterized by projections
and clefts, whereas in TNBS-treated samples the epithelium appeared smooth and the
lumen was expanded. In the mid-intestine region, higher numbers of goblet cells were
observed in TNBS-exposed fish compared with controls. Histological analysis did not
show epithelial architecture disruption in the posterior intestine of both control
and TNBS-exposed groups. In addition, goblet cells were observed in the regions of
intestinal bulb and posterior intestine of larvae exposed to TNBS, while the presence
of goblet cells remained restricted to the mid-intestine in the control.

The increase in goblet cells observed in TNBS-exposed larvae was further detected
using AB-PAS staining as described above. As it is shown in Figure 3A, the number of goblet cells significantly increased with time and in a dose-dependent
pattern. Representative pictures of maximum and minimum numbers of goblet cells in
all 3 regions of the intestinal tract were shown in Figure 3B.

Figure 3.Quantification of goblet cells stained with Alcian blue and periodic acid Schiff reagent
(AB–PAS). A: Goblet cell number increased with increasing concentrations of TNBS over time. All
error bars represent as mean ± SEM. n=10 larvae per group, aIndicates a significant difference (p<0.05) between TNBS-exposed group (25 μg/ml) and the control, bIndicates a significant difference (p<0.05) between TNBS-exposed group (50 μg/ml) and the control, cIndicates a significant difference (p<0.05) between TNBS-exposed group (75 μg/ml) and the control, dIndicates a significant difference (p<0.05) between control groups at 6 dpf and 4 dpf, eIndicates a significant difference (p<0.05) between control groups at 8 dpf and 4 dpf. B: Representative pictures of maximum and minimum numbers of goblet cells in the intestinal
bulb, the mid-intestine and the posterior intestine. Histochemical staining with AB–PAS
demonstrates that goblet cells continue to synthesize acidic mucins.

Inflammatory cytokine production in larvae exposed to TNBS

TNF-α expression was examined using immunofluorescence to measure inflammatory reactions
in larval zebrafish exposed to TNBS. In our study, TNF-α appeared as red fluorescent
light in plasma around the nucleus within the intestinal epithelium (Figure 4A). In the control groups, TNF-α staining is absent from the gut (Figure 4A and B). However, TNF-α expression was stimulated significantly with increasing concentrations
of TNBS (Figure 4B). In addition, larvae exposed to the same dose of TNBS, TNF-α immunofluorescence
levels increased as the exposure time grew (Figure 5B). It proved TNBS exposure primarily evoked an inflammatory response within the intestine
dose and time dependently.

Figure 4.Immunofluorescence analysis of TNF-α expression in gut. A: TNF-α expression was stimulated in larvae exposed to TNBS. TNF-α staining (red)
and DAPI staining (blue) images were visualized by confocal laser scanning microscopy.
Bars: 25 μm. B: TNF-α immunofluorescence levels increased with increasing concentrations of TNBS
over time. All error bars represent as mean ± SEM, n=13–16 sections per group, aIndicates a significant difference (p<0.05) between TNBS-exposed group (25 μg/ml) and the control, bIndicates a significant difference (p<0.05) between TNBS-exposed group (50 μg/ml) and the control, cIndicates a significant difference (p<0.05) between TNBS-exposed group (75 μg/ml) and the control, dIndicates a significant difference (p<0.05) between control groups at 6 dpf and 4 dpf, eIndicates a significant difference (p<0.05) between control groups at 8 dpf and 4 dpf.

Figure 5.Intestinal microbiota dysbiosis in zebrafish with TNBS-induced enterocolitis. A: Representative denaturing gradient gel electrophoresis (DGGE) profiles generated
for the gut microbiota community of zebrafish with TNBS-exposure and without it (control)
collected at 4, 6 and 8 dpf. B: Dendrogram constructed with intestinal microbiota community fingerprints based on
cluster analysis by unweighted pair group method using arithmetic averages (UPGMA).

Shifts in intestinal microbiota during TNBS-induced inflammation

The PCR-DGGE fingerprints showed changes of the composition and diversity in gut microbiota
of the twelve groups of fish (Figure 5A). The first eight lanes represent the DGGE profiles of control and TNBS-exposed
fish harvested at 4 dpf, whereas the lanes 9 to 16 represent the profiles of fish
at 6 dpf and the last twelve lanes are the profiles at 8 dpf. At each of the time
point, the gel shows the DGGE profiles of 4 groups: control (F1-F2, S1-S2, E1-E3),
25 μg/ml TNBS-exposed (F3-F4, S3-S4, E4-E6), 50 μg/ml TNBS-exposed (F5-F6, S5-S6,
E7-E9) and 75 μg/ml TNBS-exposed (F7-F8, S7-S8, E10-E12).

The dendrogram based on DGGE banding similarity patterns showed that samples from
different time points were separated into three different clusters (Figure 5B), indicating the establishment of the gut microbiota during zebrafish development
from 4 to 8 dpf. At 8 pdf, the microbial composition in the control and TNBS-exposed
groups especially the 75 μg/ml TNBS-exposed group had a significant variation, whereas
at 4 and 6 dpf, the community profiles were not clearly distinct. It revealed TNBS
exposure resulted in intestinal microbiota alteration by 8 pdf.

The alternations of Shannon-Wiener diversity indices according to the intensity of
bands were showed in Figure 6. As we can see, during the bacterial colonization of the zebrafish gut from 4 to
8 dpf, the biodiversity of intestinal microbiota was increased. Meanwhile, larvae
exposed to TNBS had a lower community diversity of gut bacteria compared to control
group at 8 dpf.

Figure 6.Biodiversity of microbiota composition in zebrafish with TNBS-induced IBD. All error bars represent as mean ± SEM. n=6 samples per group, aIndicates a significant difference (p<0.05) between TNBS-exposed group (25 μg/ml) and the control, bIndicates a significant difference (p<0.05) between TNBS-exposed group (50 μg/ml) and the control, cIndicates a significant difference (p<0.05) between TNBS-exposed group (75 μg/ml) and the control, dIndicates a significant difference (p<0.05) between control groups at 6 dpf and 4 dpf, eIndicates a significant difference (p<0.05) between control groups at 8 dpf and 4 dpf.

Bacterial species associated with inflammatory disorder

In order to define the key members of intestinal microbiota that likely contributed
to the pathogenesis of TNBS-induced inflammatory disorder, we further identified the
alteration of the dominant bacterial species in zebrafish gastrointestinal tract.
Nineteen sequences of 16S rRNA gene fragments were obtained and sequenced. These genes
were assigned to 19 bacterial phylotypes based on the highest sequence similarity
(95–100%) matched to GenBank sequences obtained by BLAST analysis (Figure 5A, Table 2). We next quantified the relative abundance of fragments in DGGE profiles of the
19 bacterial phylotypes (Figure 7).

Figure 7.The relative abundance of predominant bacteria in zebrafish intestine. A: The mean richness of DGGE bands from the control samples collected at 4, 6 and 8
dpf. B: The mean richness of DGGE bands from the samples exposed to different TNBS concentrations
(0, 25, 50 and 75 μg/ml) collected at 8 dpf. The staining intensity of fragments was
expressed as a proportion (%) of the sum of all fragments in the same lane. Rf, relative
front.

As shown in Figure 7A, the composition of the bacterial community in larvae digestive tract changed over
time to become dominated by the bacterial phyla of Proteobacteria and Firmicutes. In particular, the proportions of Proteobacteria phylum, including Hydrocarboniphaga daqingensis (L11), Limnobacter sp. (L13), Comamonas sp. (L16), Salmonella sp. (L17) and Aeromonas caviae (L19), were dramatically increased from 4 dpf to 8 dpf (p<0.01).

Meanwhile, the significant alterations in the abundance of the 19 bacterial phylotypes
between the TNBS-exposed groups and controls at 8 dpf were revealed (Figure 7B). The sections of Proteobacteria , such as Hydrocarboniphaga daqingensis(L11), Limnobacter sp. (L13), Citrobacter freundii (L14), Comamonas sp. (L16) and Salmonella sp. (L17), showed an increase in relative richness in the gut microbiota of zebrafish
exposed to TNBS as comparison with the control group (p<0.01). However, Citrobacter werkmanii (L18) was less abundant in TNBS-exposed groups than in the control (p<0.05). In addition, Firmicutes bacteria consisting of Lactococcus plantarum (L6), and Streptococcus sp. (L9) were less present in TNBS-exposed fish (p<0.05).

Quantitative real-time PCR was performed to verify the changes found by DGGE. The
toltal number of bacteria was significantly increased from 4 dpf to 8 dpf (p<0.001, Figure 8A). However, no differences in total number of bacteria were found between TNBS-treated
groups and the control. At 8 dpf, Lactobacillus group was significantly reduced in the TNBS-exposed groups (Figure 8B). Numbers of Burkholderia increased significantly (Figure 8D), but not Enterobacteriaceae family (Figure 8C). Which was consistent with the DGGE result.

Figure 8.Quantitative analysis of characteristic bacterial species. The relative quantity of specific groups of bacteria was determined by real-time
PCR of 16S rRNA gene of (A)Total bacteria, (B)Lactobacillus group, (C)Burkholderia and (D)Enterobacteriaceae family. All reactions were performed in triplicate. Specific bacteria 16S rRNA gene amount
was normalized to total bacteria 16S rRNA. Quantification values were represented
as mean ± SEM log 16S rRNA gene copies per 10 ng of bacterial genomic DNA. aIndicates a significant difference (p<0.05) between TNBS-exposed group (25 μg/ml) and the control, bIndicates a significant difference (p<0.05) between TNBS-exposed group (50 μg/ml) and the control, cIndicates a significant difference (p<0.05) between TNBS-exposed group (75 μg/ml) and the control, dIndicates a significant difference (p<0.05) between control groups at 6 dpf and 4 dpf, eIndicates a significant difference (p<0.05) between control groups at 8 dpf and 4 dpf.

Enterocolitis severity and TNF-α expression correlate with the composition in gut
microbiota

We had observed the severity of enterocolitis in TNBS-treated zebrafish increased
in a dose-dependent pattern at 8 dpf as compared with contols (Figure 2), whereas the abundance of Proteobacteria (especially Burkholderia) dramatically increased and the proportion of Firmicutes (Lactobacillus group) decreased significantly (Figure 8). We may predict that colitis severity would correlate with TNBS-induced changes
in composition of gut bacteria. Accordingly, we calculated the correlation between
enterocolitis scores and the density of Burkholderia and Lactobacillus group separately by Pearson correlation analysis. We found that the colitis scores correlated
with the abundance of Burkholderia (p=0.0045, Figure 9A) and the richness of Lactobacillus group (p=0.006, Figure 9B). These findings demonstrate that TNBS-induced enterocolitis correlate with changes
in the composition and density of the gut microbiota.

In the same way, we generated the correlation between TNF-α expression and TNBS-induced
alterations in of gut microbiota. It came to the same conclusion that TNF-α expression
correlated with the density of Burkholderia and Lactobacillus group and intestinal microbiota diversity, separately (Figure 9C, D).

Phylogenetic analysis of the predominant bacteria

A phylogenetic tree depicting the evolutionary correlations among 19 bacteria and
some of their relatives available in GenBank (similarity>95%), inferred on the basis
of aligned 16S rDNA sequences, is shown in Figure 10. It showed that the dominant sequences from the zebrafish gut were phylogenetically
clustered into 2 phylum: Firmicutes (total 9 sequences: 7 of Lactobacillales, 1 of Clostridiales and 1 of Uncultured bacterium) and Proteobacteria (total 10 sequences: 7 of γ-Proteobacteria, 2 of β-Proteobacteria and 1 of Uncultured bacterium).

Figure 10.Phylogenetic analysis based on partial 16S rRNA gene sequences of predominant bacterial
species in the gut of zebrafish obtained from this study and some of those available
in GenBank. Identification and GenBank accession numbers are indicated for each sample. The evolutionary
history was inferred using the Neighbor-Joining method. The optimal tree with the
sum of branch length = 4.46466368 is shown. The evolutionary distances were computed
using the Maximum Composite Likelihood method and are in the units of the number of
base substitutions per site. Codon positions included were 1st+2nd+3rd+Noncoding.
All positions containing gaps and missing data were eliminated from the dataset (Complete
deletion option). There were a total of 62 positions in the final dataset. Phylogenetic
analyses were conducted in MEGA4.

Discussion

In the present study, we established a zebrafish model organism to mimic human IBD
using TNBS originally described by Fleming et al. It is confirmed that gut physiology
and pathology relevant to this human disease state can be rapidly modeled following
TNBS exposure, including intestinal epithelial damage, increase in goblet cells, production
of inflammatory cytokines and intestinal microbiota dysbiosis. From the histological
assessment of damage severity in the gut it was apparent that all larvae from the
healthy control group showed no overt features of enterocolitis, while larvae exposed
to TNBS exhibited pathological features consistent with enterocolitis time- and dose-
dependently. The results present a detailed characterization of the development of
intestinal inflammation in TNBS-treated larval zebrafish and establish a basis for
using zebrafish to explore unique bacterial communities involved in the pathogenesis
of IBD.

The aim of this study was to characterize the intestinal microbiota dysbiosis in the
gut of zebrafish with IBD induced by TNBS, and to identify individual bacterial species
that contribute to these dysbiosis. It is widely believed that IBD involves a breakdown
in relations between the host immune response and microbial population resident in
the GI tract. Reduced richness or diversity of bacterial species has been reported
widely in patients with ulcerative colitis and Crohn’s disease, as well as in animal
models with IBD, which was consistent with our observation [6,8]. It could be hypothesized that, from its gut microbial community composition, the
healthy larvae may have been more likely to format a stable micro-ecosystem with the
intestinal environment, the gut epithelium and the mucosal immune system, therefore,
less susceptible of developing IBD. Most studies suggest that the gut microbiota is
an important factor in the pathogenesis of IBD, however, little is known about the
contributions of particular intestinal species to health and disease.

Recently, increasingly molecular profiling techniques are being employed for the detection
and characterization of the unculturable bacteria in the human colon. Studies based
on DGGE have shown a faecal microbiota dysbiosis signature associated with CD, characterised
by a decreased presence of Faecalibacterium prausnitzii, Bifidobacterium adolescentis, Dialister invisus, an unknown Clostridium sp. and an increased presence of Ruminococcus gnavus[24]. Others revealed that Bacteroides vulgatus, Bacteroides uniformis, and Parabacteroides sp. were more commonly present at higher levels in healthy controls than in UC or IBD
patients [25]. The changes of the intestinal microbiota in IBD patients were not only investigated
in Western population, but also a research on the faecal bacterial dysbiosis in Chinese
CD patients showing an increase of the richness γ-Proteobacteria (especially Escherichia coli and Shigella flexneri) and a reduced proportion of Bacteroides and Firmicutes[26]. Such differences were also observed by others applying terminal restriction fragment
length polymorphism (T-RFLP) and fluorescent in situ hybridization (FISH) [27-29]. In murine models of IBD, Bacteroidales (Bacteroides sp., Alistipes, Butyricimonas, Odoribacter, and Parabacteroides sp.) and Lactobacillus sp. were predominantly associated with the DSS-induced colitic and healthy rats, respectively
[30]. Obviously, there were significant differences between the experimental sets from
which samples were sourced. This may be caused by many factors including genetics,
variations in environmental conditions from different geographic locations, as well
as the microbiological status of food and water. Despite these differences, most of
the studies have shown an increase of some opportunistic pathogenic Proteobacteria and a decreased proportion of Firmicutes phylum in CD, UC, or IBD.

The role of the microbiota in the zebrafish larval TNBS model has not been previously
described. Our results showed that the dominant bacterial species were altered in
the larvae intestine with TNBS-induced IBD, which was characterized by an overrepresentation
of Proteobacteria and a relative lack of Firmicutes phylum. We observed that Limnobacter sp., Comamonas sp. and Salmonella sp., major members of Proteobacteria, had a significantly elevated abundance and became to be dominant in the samples
from TNBS-treated groups. This is consistent with previous reports in IBD, which suggests
that the host-microbial interactions are evolutionarily conserved and bacterial communities
within the zebrafish intestines contribute the same to IBD etiology as in mammals.
This work thus highlights the potential use of zebrafish in the study of gut microbial
contributions to the pathogenesis of IBD and also other intestinal disorders. In fact,
the zebrafish has shown several unique advantages that make it superior to other animal
model organisms for microbial investigation. To start with, the composition of the
mucosal- and luminal-associated/faecal microbiota has been shown to be significantly
different in human digestive tract [31,32]. Some believe the mucosal-associated microbiota seems of a closer link to the disease
process than the faecal microbiota, as IBD is a disorder of mucosal inflammation.
For a better understanding, characterisation of the mucosal-associated bacteria is
therefore required. However, investigations are limited due to the difficulties of
sampling of mucosal biopsy from healthy people. Besides, there is no conclusion whether
the mucosal- or luminal-associated microbiota represents the accurate composition
of the microbiota from patients with IBD. In contrast, our samples contain both the
luminal- and mucosal-associated microbiota of the entire GI tract, which could reveal
a better picture of the intestinal microbiotal composition. Furthermore, there was
significant inter-individual variation in gut bacterial composition among both healthy
and IBD groups in either humans or animal models research. The high inter-individual
variability may cause confusion whether the microbiota shifts owing to the disease
or the lifestyle and environmental changes. Whereas in zebrafish models, as each sample
contains about 20 larvae, the individual differences could be greatly eliminated and
more focusing on the differences in microbial communities between IBD groups and the
healthy control. Finally, although studies have indicated a role for the microbiota
in IBD development, to further understand this relationship between microbiota and
host immunity and its degradation in inflammatory disease of the intestine, the next
step must surely involve signaling pathways and molecular mechanisms through which
the host recognizes gut microbiota and stimulates inflammatory processes. Rodent studies
indicate that initial recognition of microbiota in the extracellular environment occurs
via pathogen-recognition receptors (PRRs), which recognize microbial-associated molecular
patterns (MAMPs) [33,34]. Some studies have shown that TLR4 knockout mice did not develop enterocolitis upon
treatment with DSS and TLR4 antagonist antibody ameliorates inflammatory response
in colitic mice [35,36]. In addition, a meta-analysis revealed that genetic variations in TLR4 presented
a statistically significant risk of developing CD and UC [37]. It is reasonable to speculate that gut microbiota play a role in the development
of IBD via TLR signaling pathways. In zebrafish models, reverse genetic analyses using
target-selected mutagenesis or antisense morpholino oligonucleotides (MOs) provide
additional means for identifying molecular mediators of host–bacterial relationships
in the gut [38,39]. The completion of the zebrafish genome will facilitate these approaches and many
more recently studies show the feasibility of studying host–microbial interactions
in genetically engineered zebrafish.

Conclusions

In summary, we represented for the first time the molecular characteristics of intestinal
microbiota dysbiosis in larval zebrafish with TNBS-induced IBD-like colitis. The present
study defined a reduced biodiversity of gut bacterial community in IBD-like colitis.
The intestinal microbiota dysbiosis in zebrafish IBD-like models was characterized
by an increase of Proteobacteria and a reduced proportion of Firmicutes. The major challenge here is elucidating whether alterations in the gut microbial
composition represent cause, or consequence, of host inflammation and disease state
in IBD. In deed, it could be hypothesize that the chemicals, eg, TNBS, oxazolone,
or DSS, affect the microbiota composition and then alterations in the microbial community
initiate mucosal immune-mediated inflammation via TLRs signaling pathways. It is possible
that changes in gut microbial ecology are crucial determinants in the susceptibility
to experimental enterocolitis. However, in the present study, we observed that the
intestinal epithelial damage and the overproduction of inflammatory cytokine (TNF-α)
appeared ahead of the intestinal microbiota shifts. This may suggest that the chemicals
initiate inflammation and the progressive inflammatory damage to the host intestinal
mucosa applies pressure on the intestinal microbiota that further shifts community
structure. Or the host and the microbiota interact in both ways and there is a feedback
loop that perpetuates the inflammation. In characterizing these changes in community
structure and function, it may be possible to provide new clues into determining the
aetiological mechanisms of IBD and alter these events to prevent or ameliorate the
disease.

Methods

Ethics statement

All experiments with zebrafish were performed in strict accordance with the recommendations
in the Guide for the Care and Use of Laboratory Animals of the National Institutes
of Health. The protocols were approved by the Institutional Animal Care and Use Committee
of Model Animal Research Center, Nanjing University (MARC-AP#: QZ01), in accordance
with the Guideline on the Humane Treatment of Laboratory Animals in China and the
Regulations for the Administration of Affairs Concerning Experimental Animals.

Zebrafish maintenance and embryo collection

Wild-type (AB strain) zebrafish were reared at 28±0.5°C on a 14-h light/10-h dark
cycle in a closed flow-through system in charcoal-filtered and fully aerated tap water
according to standard procedures [40]. The fish were fed with commercial flakes twice daily.

Zebrafish embryos were collected from spawning adults in groups of about 16 males
and 8 females in tanks overnight. Spawning was induced in the morning shortly after
the light was turned on. Collected embryos were maintained in embryo medium (13.7 mM
NaCl, 0.54 mM KCl, 1.3 mM CaCl2, 1.0 mM MgSO4, 0.25 mM Na2H PO4, 0.44 mM KH2 PO4, 0.42 mM NaHCO3) at 28.5°C. At 4–5 hours post-fertilization (hpf), those embryos that had developed
normally and reached the blastula stage were selected under a dissecting microscope
for subsequent experiments.

Induction of IBD by TNBS exposure

A stock solution of 5% (w/v) 2, 4, 6-trinitrobenzenesulfonic acid (TNBS; Sigma, St
Louis, USA) in embryo medium was used for the induction of IBD. Zebrafish from 3 days
post fertilization (dpf) were randomly placed into groups of 15 larvae in 20 ml of
exposure solution (embryo medium containing 0, 25, 50 and 75 μg/mL TNBS). The range
of concentrations was selected based on previously ascertained range-finding studies
and information from the available literatures [14,15]. A 90% (v/v) water change was performed each day starting at 3 pdf when larvae hatch
from their chorions. Samples were collected at 4, 6 and 8 days postfertilization (dpf).

Histology

Larval zebrafish from 4 dpf, 6 dpf and 8 dpf were anesthetized by immersion in 0.2 mg/ml
3-amino benzoic acid ethylester (MS222, Sigma). For histology, samples were fixed
in Bouin’s Fixative overnight at 4°C and mounted in SeaPlaque 1% low-melting point
agarose. Then samples were dehydrated through a standard series of alcohols and Histo-clear
and embedded in paraffin. 5 μm sections were cut for staining with hematoxylin and
eosin. Histological sections were imaged and photographed with an Olympus CX41 system
microscope (Olympus USA, Center Valley, PA, USA) and the DS-5 M-L1 digital sight camera
system (Nikon, Japan). The enterocolitis scores were quantified by an observer who
was blinded to the prior treatment of the fish. And these data represent three independent
experiments.

Detection of goblet cells using AB-PAS staining

For goblet cell quantification, 5-μm paraffin sections were prepared as described
in the Methods and stained sequentially with 1% Alcian blue pH 2.5 for 15 min, 1%
aqueous periodic acid for 10 min and Schiff’s reagent for 10–15 min. Using this method,
goblet cells stain blue. The number of goblet cells was counted manually along the
length of the gut from the intestinal bulb to the anus.

For immunofluorescence, 5-μm frozen sections were cut and blocked with 1% bovine serum
albumin prior to being incubated with anti-TNF-α(IN), Z-Fish™, Catalog No. 55383P
(1:150, 100 μg/400 μl, AnaSpec, Fremont, CA) overnight at 4°C. Sections were washed
in PBS and incubated with Alexa Fluor 488-conjugated anti-mouse secondary antibodies
(1:150, Invitrogen, La Jolla, CA) for 30 minutes at 4°C, followed by counterstained
with DAPI (1:500). Sections were imaged and photographed with Leica TCS SP5 confocal
scanning microscope (Leica Microsystems, Heidelberg GmbH, Mannheim, Germany). The
intensity of TNF-α immunofluorescence was quantified for each treatment group, with
a minimum of 6 samples per group, using color threshold and area measurements with
AnalySis software.

Microbial analysis by denaturing gradient gel electrophoresis (DGGE)

The DGGE analysis was carried out to identify the microbial community in the intestine
and to study the potential changes between the different groups of zebrafish.

Extraction of DNA and PCR amplification

Bacterial DNA was extracted from pools of 20 zebrafish larvae using the QIAamp DNA
Stool Mini Kit (QIAGEN, Hilden, Germany) according to the manufacturer’s protocol,
and stored at −20°C until use.

PCR was performed on an Applied Biosysterm 2720 Thermal Cycler as a touchdown PCR.
The hypervariable V3 region of the 16S ribosomal DNA gene was amplified using polymerase
chain reaction (PCR) with forward primer (GC357f 5′CGCCCGGGGCGCGCCCCGGGCGGGGCGGGGGCACGGGGGGATTACCGCGGCTGCTGG3′)
and reverse primer (518r 5′CCTACGGGAGGCAGCAG3′). The PCR reaction mixtures consisted
of 2 μl of extracted bacterial DNA, 5 μl of 10×PCR buffer, 1 μl of dNTP mixture (2.5 mM
each), 1 μl of each primer (10 pM), 0.5 μl of Taq-Polymerase (5 U/μl) and sterile water to final volume of 50 μl. The cycling program
was as follows: predenaturation at 94°C for 5 min, followed by 20 cycles of 94°C for
30 s, 65°C for 30 s decreased by 0.5°C for each cycle, and 68°C for 30 s, after which
10 additional cycles of 94°C for 30 s, 55°C for 30 s, and 68°C for 30 s were carried
out, and a final extension at 68°C for 7 min, soak at 4°C.

Integrity of PCR products was determined by running agarose gel electrophoresis, and
the quantity was determined using QubitTM fluorometer (Invitrogen, NY, USA).

Denaturing gradient gel electrophoresis

DGGE was performed on the PCR products from DNA samples using 16 cm × 16 cm ×1 mm
gels with a DCode Universal Mutation Detection System (Bio-Rad, Hercules, CA). A 35-50%
urea and formamide denaturing gradient and 8% polyacrylamide gel (37.5:1 acrylamide-bisacrylamide)
were used. The gradient was prepared using the gradient delivery system (Bio-Rad),
following the manufacturer’s protocol. A 100% denaturant solution contained 7 M urea
and 40% formamide. Gels were run in 1×TAE (20 mM Tris, 10 mM acetate, 0.5 M EDTA,
pH 7.4) at 60°C, first at 200 V for 10 minutes and then at 120 V for 7.5 hours. The
resulting gels were stained with SYBR Green I (Invitrogen) for 30 min, visualized
and photographed using the Gel Doc EQ system (Bio-Rad, USA). All gels were normalized
using a reference sample with bands distributed throughout the whole gel.

Analysis of DGGE profile

Gel images were aligned using Adobe Photoshop CS5 by running common samples on both
outer sides of each gel, to allow comparison of two gels in one profile. DGGE profiles
were analysed using Quantity One software (version 4.6; Bio-Rad Laboratories, Hercules,
CA). The lanes were identified, and their background intensities were removed using
the rolling disk method described in the program. Then bands were detected automatically
by the software, followed by manual correction if necessary, and they were matched
at 0.5% tolerance level. The tolerance level is the minimum spacing that the matching
model expects to find between unique bands, and it is expressed as a percentage of
lane height. The relative quantity of bands is expressed as a proportion (%) relative
to the sum of the intensities of all of the bands in the same lane. A similarity matrix
was computed by comparing the profiles of lanes, and the percentage similarity was
expressed as the Dice coefficient. The presence or absence of a band in a lane was
considered. Identical profiles have a percentage similarity of 100. Unweighted pair
group method using arithmetic averages (UPGMA) was used to compare the similarity
of samples in a dendrogram. The general diversity of bacterial communities was calculated
by generating Shannon’s index of diversity on quantitative information [41].

Sequencing of DGGE bands

Bands of interest from DGGE gels were excised and immersed in 20 μl of sterile water
and left overnight at 4°C. 2 μl of eluted DNA from each band was used as template
for PCR re-amplification with the forward primer (without GC clamp) (357f 5′- ATTACCGCGGCTGCTGG
-3′) and the reverse primer (518r 5′-CCTACGGGAGGCAGCAG-3′). PCR was performed in a
50 μl reaction mixture including 2 μl of template DNA, 5 μl of 10×PCR buffer, 1 μl
of dNTP mixture (2.5 mM each), 1 μl of each primer (10 pM), 0.5 μl of Taq-Polymerase
(5 U/μl) and 39.5 μl sterile water. Amplification was performed under the following
conditions: 94°C for 5 min, 20 cycles of 94°C for 30s, 65°C for 30s decreased by 0.5°C
for each cycle, and 68°C for 30 s, additional 15 cycles of 94°C for 30 s, 55°C for
30 s, and 68°C for 30 s, with a final extension at 68°C for 7 min.

After the PCR products were purified (QIAquick PCR Purification Kit, QIAGEN) and quantified
(Qubit fluorometer, Invitrogen), the sequence analysis of the products was carried
out using the Sanger’s method on an ABI 3730 automated sequencing system. The sequences
obtained were then aligned with NCBI GenBank databases using the BLAST tool. The phylogenetic
tree was constructed using the MEGA 4.0 program in the method of neighbor-joining
based on evolutionary distances.

Quantitative real-time PCR analysis

Bacterial species that characterize the predominant intestinal dysbiosis in zebrafish
larvae with TNBS-induced enterocolities derived from the DGGE comparative analyses
were quantified by quantitative PCR using the 7300 Real-Time PCR System (Applied Biosystems,
USA). A reaction mixture (20 μl) consisted of 1 μl of DNA (10 ng), 0.4 μl of each
primer, 10 μl 2×SYBR. The primers and probes based on 16S rRNA gene sequences were
chosen to target total bacteria, Lactobacillus group, the dominant group of Firmicutes, Enterobacteriaceae family and Burkholderia species, the main Proteobacteria phylum in zebrafish gut. Total bacterial 16S rRNA gene copies
were quantified with primers (Bact1369; 5′CGGTGAATACGTTCYCGG3′and Prok1492; 5′GGWTACCTTGTTACGACTT3′).
PCR was performed with an initial denaturation step of 95°C for 3 min, followed by
40 cycles of 95°C for 15 s, 56°C for 30 s and 72°C for 30 s. Lactobacillus group were quantified using the combination of forward, (LAC1; 5′AGCAGTAGGGAATCTTCCA3′),
and reverse primer, (Lab0677; 5′CACCGCTACACATGGAG3′) in a cycling program where after
the initial denaturation 95°C for 3 min, 40 cycles were applied at 95°C for 30 s,
and binding and extension at 60°C for 1 min. Primer (Eco1457F; 5′CATTGACGTTACCCGCAGAAGAAGC3′)
combined with primer (Eco1652R; 5′CTCTACGAGACTCAAGCTTGC3′) were used for the quantification
of Enterobacteriaceae family with the following conditions: an initial DNA denaturation step at 95°C for 5 min,
followed by 40 cycles of denaturation at 95°C for 15 s, and primer annealing and extension
at 72°C for 30 s. Burkholderia species were quantified using the forward primer (Burk3; 5′CTGCGAAAGCCGGAT3′) and the reverse
primer (BurkR; 5′TGCCATACTCTAGCYYGC3′) with the following cycling conditions: predenaturation
at 95°C for 4 min; 60 cycles of 94°C for 1 min, 62°C for 90 s decreased by 1°C for
every fifth cycle, after which 25 additional cycles were carried out at 58°C, and
72°C for 2 min, and a final extension at 72°C for 10 min. Data analysis was proceeded
with Sequence Detection Software version 1.6.3 ( Applied Biosystems). All reactions
were performed in triplicate. Specific bacteria 16S rRNA gene amount was normalized
to total bacteria 16S rRNA. Quantification values were represented as mean (SEM) log
16S rRNA gene copies per 10 ng of bacterial genomic DNA.

Statistical analysis

Biochemical measurements were performed at least in duplicate. Quantitative histological
analyses were performed by a blinded scorer. Results are presented as mean ± standard
error of the mean. Survival curve comparison calculations used the Gehan-Breslow-Wilcoxon
test. Two-way anova was applied to analyze the data to understand the combined effect
of the two factors - time and treatment. Bonferroni multiple comparison post hoc tests
were used to find the significant differences between the means at a particular time
point⁄treatment. Pearson correlation, α =0.05, was used to assess linear relationships
between enterocolitis score/inflammatory cytokine expression level and intensity/diversity
in gut microbiota. All statistical analyses were performed with Graph-Pad Prism version
5.0 (GraphPad Software, San Diego, CA), and the significant differences are reported
at P < 0.05.

Nucleotide sequences accession number

The sequences of 16S rRNA gene obtained in this study have been deposited in the GenBank
database (EMBL, U.K.) under accession numbers KF515539-KF515557.

Competing interests

The authors declared that they have no competing interests.

Authors’ contributions

QH carried out the zebrafish model-building, the sequence analysis and drafted the
manuscript. LW participated in the Immunofluorescence analysis. FW and CYW participated
in the sequence alignment. CT participated in the histological analysis. QRL and JSL
conceived of the study, and participated in its design and coordination and helped
to draft the manuscript. All authors read and approved the final manuscript.

Acknowledgments

This work was supported by the Key Project of National Natural Science Foundation
in China (30830098), National Natural Science Foundation in China (81070375), National
Basic Research Program (973 Program) in China (2009CB522405), National High-tech R&D
Program (863 Program) of China (2012AA021007) and Scientific Research Fund in Jiangsu
Province (BK2009317). We thank Prof. Qingshun Zhao providing the zebrafish and embryos.

Hudcovic T, Stepankova R, Cebra J, Tlaskalova-Hogenova H: The role of microflora in the development of intestinal inflammation: acute and chronic
colitis induced by dextran sulfate in germ-free and conventionally reared immunocompetent
and immunodeficient mice.